Results 251 to 260 of about 19,772 (299)

Oculomotor and Caloric Test Findings in 122 Patients With Unilateral Vestibular Schwannoma. [PDF]

Cureus
Narayana Swamy S, Yuvaraj P, Pradyumna RM, Pruthi N, Ar P, Thennarasu K, N P, Rajasekaran AK.   +7 more
europepmc   +1 more source

Improved Somatotopic Consistency of EEG Source Localization Using a Personalized Segmentation-Free Head Model. [PDF]

Brain Topogr
Tada Y, Hirata A, Kubota Y, Fukunaga M, Wasaka T.   +4 more
europepmc   +1 more source

Exploring the use of a virtual patient model for teaching clinical empathy to medical students at a tertiary care institute: a cross-sectional study. [PDF]

J Rural Med
Sharma V, Mahadule AA, Goel A, Mittal S, Patil PM, Mohan L.   +5 more
europepmc   +1 more source

Amplitude Versus Angle (AVA) feature restoration in prestack gathers via dictionary learning. [PDF]

PLoS One
Gao Y, Shi X, Zhang D, Wang C, Zhang R, Feng Y.   +5 more
europepmc   +1 more source

Subspace pursuit embedded in Orthogonal Matching Pursuit

TENCON 2012 IEEE Region 10 Conference, 2012
Orthogonal Matching Pursuit (OMP) is a popular greedy pursuit algorithm widely used for sparse signal recovery from an undersampled measurement system. However, one of the main shortcomings of OMP is its irreversible selection procedure of columns of measurement matrix.
Sooraj K. Ambat, Saikat Chatterjee, K.V.S. Hari   +2 more
core   +3 more sources

Optimized orthogonal matching pursuit approach [PDF]

IEEE Signal Processing Letters, 2002
An adaptive procedure for signal representation is proposed. The representation is built up through functions (atoms) selected from a redundant family (dictionary).
L Rebollo-Neira
exaly   +2 more sources

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Matching Pursuit of Images

Proceedings of IEEE-SP International Symposium on Time- Frequency and Time-Scale Analysis, 1998
A crucial problem in image analysis is to construct efficient low-level representations of an image, providing precise characterization of features which compose it, such as edges and texture components. An image usually contains very different types of features, which have been successfully modelled by the very redundant family of 2D Gabor oriented ...
F. Bergeaud, Stéphane Mallat
openaire   +1 more source

Multiplivative matching pursuit

2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002
This paper introduces a novel nonlinear low-level representation of an image with signal-dependent noise. For multiplicative noisy image, we introduce an algorithm called multiplicative matching pursuit decomposition (MMPD), that decomposes the signal containing the intrinsic variation into a nonlinear expansion of waveforms that are selected from a ...
Amina Serir, Jean-Christophe Pesquet
openaire   +1 more source